JMP® Start Statistics: A Guide to Statistics and Data Analysis Using JMP®
by Sheila Loring, Ann Lehman, Mia L. Stephens, John Sall
JMP Start Statistics, 6th Edition
- Preface
- 1 Preliminaries
- 2 Getting Started with JMP
- 3 Data Tables, Reports, and Scripts
- 4 Formula Editor
- 5 What Are Statistics?
- 6 Simulations
- 7 Univariate Distributions: One Variable, One Sample
- Overview
- Looking at Distributions
- Describing Distributions of Values
- Statistical Inference on the Mean
- Practical Significance versus Statistical Significance
- Examining for Normality
- Special Topic: Practical Difference
- Special Topic: Simulating the Central Limit Theorem
- Seeing Kernel Density Estimates
- Exercises
- 8 The Difference Between Two Means
- Overview
- Two Independent Groups
- When the Difference Isn’t Significant
- Check the Data
- Launch the Fit Y by X Platform
- Examine the Plot
- Display and Compare the Means
- Inside the Student’s t-Test
- Equal or Unequal Variances?
- One-Sided Version of the Test
- Analysis of Variance and the All-Purpose F-Test
- How Sensitive Is the Test?
- How Many More Observations Are Needed?
- When the Difference Is Significant
- Normality and Normal Quantile Plots
- Testing Means for Matched Pairs
- Two Extremes of Neglecting the Pairing Situation: A Dramatization
- A Nonparametric Approach
- Exercises
- 9 Comparing Many Means: One-Way Analysis of Variance
- 10 Fitting Curves through Points: Regression
- 11 Categorical Distributions
- 12 Categorical Models
- Overview
- Fitting Categorical Responses to Categorical Factors: Contingency Tables
- Two-Way Tables: Entering Count Data
- If You Have a Perfect Fit
- Special Topic: Correspondence Analysis— Looking at Data with Many Levels
- Continuous Factors with Categorical Responses: Logistic Regression
- Surprise: Simpson’s Paradox: Aggregate Data versus Grouped Data
- Generalized Linear Models
- Exercises
- 13 Multiple Regression
- 14 Fitting Linear Models
- Overview
- The General Linear Model
- Types of Effects in Linear Models
- Coding Scheme to Fit a One-Way ANOVA as a Linear Model
- Regressor Construction
- Interpretation of Parameters
- Predictions Are the Means
- Parameters and Means
- Analysis of Covariance: Continuous and Categorical Terms in the Same Model
- The Prediction Equation
- The Whole-Model Test and Leverage Plot
- Effect Tests and Leverage Plots
- Least Squares Means
- Lack of Fit
- Separate Slopes: When the Covariate Interacts with a Categorical Effect
- Two-Way Analysis of Variance and Interactions
- Optional Topic: Random Effects and Nested Effects
- Exercises
- 15 Design of Experiments
- 16 Bivariate and Multivariate Relationships
- 17 Exploratory Modeling
- 18 Control Charts and Capability
- 19 Mechanics of Statistics
- A Answers to Selected Exercises
- Chapter 4, “Formula Editor”
- Chapter 7, “Univariate Distributions: One Variable, One Sample”
- Chapter 8, “The Difference Between Two Means”
- Chapter 9, “Comparing Many Means: One-Way Analysis of Variance”
- Chapter 10, “Fitting Curves through Points: Regression”
- Chapter 11, “Categorical Distributions”
- Chapter 12, “Categorical Models”
- Chapter 13, “Multiple Regression”
- Chapter 14, “Fitting Linear Models”
- Chapter 15, “Design of Experiments”
- Chapter 16, “Bivariate and Multivariate Relationships”
- Chapter 17, “Exploratory Modeling”
- Chapter 18, “Control Charts and Capability”
- B References and Data Sources
- Technology License Notices
- Index
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